{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "import os\n",
    "import sys\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "import astropy.units as u\n",
    "from astropy import wcs\n",
    "from astropy.io import fits\n",
    "from astropy.coordinates import SkyCoord\n",
    "from astropy.visualization import make_lupton_rgb\n",
    "from astropy.utils.data import download_file, clear_download_cache\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Download HSC PSF model at given position\n",
    "\n",
    "* Using the `PSF Picker` prepared by NAOJ, we can get a point spread function (PSF) model at any observed positions (RA, Dec). \n",
    "* The PSF will be delivered as a FITS image file.\n",
    "* The size of the PSF model output is `43 x 43 pixels`, which is about `7.2\" x 7.2\"`. Unfortunately you can not change the size of the PSF model.\n",
    "    - The median HSC seeing in i-band has `FWHM ~ 0.6\"`; even in the worst case, the HSC seeing still has `FWHM < 1.2\"`, so this size is good enough for most applications. \n",
    "\n",
    "* This is very similar to get the cutout image. Please see [this demo](https://github.com/dr-guangtou/unagi/blob/master/demo/demo_hsc_cutout.ipynb) for more details.\n",
    "    * **Center**: RA, Dec of position to get PSF model. Should be a `Astropy` `SkyCoord` object\n",
    "    * **Centered**: If checked, the center position of the PSF will always be the center of the image. By default (unchecked), the center position of the PSF will be the (RA, Dec) projected to the image coordinate system, and the center position will therefore be shifted by subpixel from the center of the image. Default is **True**\n",
    "    * **Type**: `coadd` or `warp`:\n",
    "        - If you select \"coadd\" (default), you will get a PSF of a coadd image. The PSF will be delivered as a single FITS image.\n",
    "        - If you select \"warp\", you will get PSFs of warped images. The PSFs will be delivered as an uncompressed tarball. \"Warp\" images are images made from CCD images by coordinate transformation. They are added pixel by pixel to be a corresponding coadd image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# Get table list from /Users/song/Dropbox/work/project/unagi/unagi/data/s20a_dud/s20a_dud_tables.fits\n"
     ]
    }
   ],
   "source": [
    "from unagi import config\n",
    "from unagi import hsc\n",
    "from unagi import plotting\n",
    "from unagi.task import hsc_psf\n",
    "\n",
    "pdr2 = hsc.Hsc(dr='pdr2', rerun='pdr2_dud')\n",
    "#pdr2 = hsc.Hsc(dr='dr3', rerun='s20a_dud')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "coord = SkyCoord(150.091344, 2.20591, frame='icrs', unit='deg')\n",
    "\n",
    "# Filters\n",
    "filters = 'i'\n",
    "\n",
    "# Output dir\n",
    "output_dir = 'data/'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Running the `hsc_psf()` task"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# Retrieving coadd PSF model in filter: i\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get single band PSF image\n",
    "\n",
    "psf_model = hsc_psf(coord, filters='i', archive=pdr2, output_dir=output_dir)\n",
    "\n",
    "_ = plotting.display_single(psf_model[0].data, scale_bar_length=1.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# Will dgenerate cutouts for a list of filters: ['g', 'r', 'i', 'z', 'y']\n",
      "# Retrieving coadd PSF model in filter: g\n",
      "# Retrieving coadd PSF model in filter: r\n",
      "# Retrieving coadd PSF model in filter: i\n",
      "# Retrieving coadd PSF model in filter: z\n",
      "# Retrieving coadd PSF model in filter: y\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x432 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get 5-band PSF models\n",
    "filter_labels = [r\"$\\rm {}$\".format(f) for f in ['g', 'r', 'i', 'z', 'y']]\n",
    "\n",
    "psf_models = hsc_psf(coord, filters='grizy', archive=pdr2, save_output=False)\n",
    "\n",
    "_ = plotting.display_all(psf_models, hdu_index=0, img_size=3, label_list=filter_labels,\n",
    "                         scale_bar_length=1.0, scale_bar_y_offset=1.5, fontsize=30, fontcolor='w')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
